Correction of catalogue and version setting

[modules/adao.git] / doc / en / ref_algorithm_Blue.rst

diff --git a/doc/en/ref_algorithm_Blue.rst b/doc/en/ref_algorithm_Blue.rst
index 248a37b6d70a4b87a96d68c3f030a08c61c4f3cd..da5e64b68ed4b0ec2b79deebf10857cc0de5a8ce 100644 (file)
--- a/doc/en/ref_algorithm_Blue.rst
+++ b/doc/en/ref_algorithm_Blue.rst
@@ -46,6 +46,7 @@ In case of non-linearity, even slightly marked, it will be easily prefered the
 Optional and required commands
 ++++++++++++++++++++++++++++++
 
+.. index:: single: AlgorithmParameters
 .. index:: single: Background
 .. index:: single: BackgroundError
 .. index:: single: Observation
@@ -94,10 +95,11 @@ following:
     :math:`(X,U)`.
 
 The general optional commands, available in the editing user interface, are
-indicated in :ref:`section_ref_assimilation_keywords`. In particular, the
-optional command "*AlgorithmParameters*" allows to choose the specific options,
+indicated in :ref:`section_ref_assimilation_keywords`. Moreover, the parameters
+of the command "*AlgorithmParameters*" allows to choose the specific options,
 described hereafter, of the algorithm. See
-:ref:`section_ref_options_AlgorithmParameters` for the good use of this command.
+:ref:`section_ref_options_Algorithm_Parameters` for the good use of this
+command.
 
 The options of the algorithm are the following:
 
@@ -106,10 +108,12 @@ The options of the algorithm are the following:
     available at the end of the algorithm. It involves potentially costly
     calculations or memory consumptions. The default is a void list, none of
     these variables being calculated and stored by default. The possible names
-    are in the following list: ["APosterioriCovariance", "BMA", "CostFunctionJ",
-    "OMA", "OMB", "Innovation", "SigmaBck2", "SigmaObs2",
-    "MahalanobisConsistency", "SimulatedObservationAtBackground",
-    "SimulatedObservationAtOptimum", "SimulationQuantiles"].
+    are in the following list: ["APosterioriCorrelations",
+    "APosterioriCovariance", "APosterioriStandardDeviations",
+    "APosterioriVariances", "BMA", "CostFunctionJ", "OMA", "OMB", "Innovation",
+    "SigmaBck2", "SigmaObs2", "MahalanobisConsistency",
+    "SimulatedObservationAtBackground", "SimulatedObservationAtOptimum",
+    "SimulationQuantiles"].
 
     Example : ``{"StoreSupplementaryCalculations":["BMA","Innovation"]}``
 
@@ -172,12 +176,30 @@ The unconditional outputs of the algorithm are the following:
 
 The conditional outputs of the algorithm are the following:
 
+  APosterioriCorrelations
+    *List of matrices*. Each element is an *a posteriori* error correlation
+    matrix of the optimal state.
+
+    Example : ``C = ADD.get("APosterioriCorrelations")[-1]``
+
   APosterioriCovariance
     *List of matrices*. Each element is an *a posteriori* error covariance
     matrix :math:`\mathbf{A}*` of the optimal state.
 
     Example : ``A = ADD.get("APosterioriCovariance")[-1]``
 
+  APosterioriStandardDeviations
+    *List of matrices*. Each element is an *a posteriori* error standard
+    deviation matrix of the optimal state.
+
+    Example : ``E = ADD.get("APosterioriStandardDeviations")[-1]``
+
+  APosterioriVariances
+    *List of matrices*. Each element is an *a posteriori* error variance matrix
+    of the optimal state.
+
+    Example : ``V = ADD.get("APosterioriVariances")[-1]``
+
   BMA
     *List of vectors*. Each element is a vector of difference between the
     background and the optimal state.